Research Article
Analysis of Users' Emotional Attitudes to Vulgar Videos Based on Data Mining
@INPROCEEDINGS{10.4108/eai.9-12-2022.2327625, author={Jinbin Yi and Yunting Miao and Yifan Tu}, title={Analysis of Users' Emotional Attitudes to Vulgar Videos Based on Data Mining}, proceedings={Proceedings of the 4th Management Science Informatization and Economic Innovation Development Conference, MSIEID 2022, December 9-11, 2022, Chongqing, China}, publisher={EAI}, proceedings_a={MSIEID}, year={2023}, month={3}, keywords={vulgar videos; data mining; user's participation behavior; sentiment analysis}, doi={10.4108/eai.9-12-2022.2327625} }- Jinbin Yi
Yunting Miao
Yifan Tu
Year: 2023
Analysis of Users' Emotional Attitudes to Vulgar Videos Based on Data Mining
MSIEID
EAI
DOI: 10.4108/eai.9-12-2022.2327625
Abstract
With the development of network video, Vulgar Videos with its unique video content and form quickly became popular, but in its early stage, there were some problems such as vulgar content and poor user experience. In order to optimize user experience, this study explores the emotional attitude of users when they participate in the Vulgar Videos based on data mining. By using Python language to write the data collection logic, run the program to crawl the microblog comment data about Vulgar Videos, use TF-IDF algorithm to extract keywords and make word frequency statistics, use SnowNLP library for sentiment analysis, build semantic network and LDA topic model, and carry out topic analysis and extraction. Meanwhile, Jieba database will be used for word co-occurrence analysis to further excavate and analyze users' emotional attitude. Through the above process, this study draws the following conclusions: Vulgar Videos not only have entertainment properties, but also social properties and information properties. From the perspective of emotion analysis, a large number of netizens hold a positive attitude towards Vulgar Videos, while a small number of users are dissatisfied with the video content.